In the proposed project, we will develop a model to predict minute-by-minute energy expenditure (EE) in children and adolescents using a new device called Actiheart, which simultaneously records heart rate (HR) and (PA). Total energy expenditure (TEE) will be derived from the summation of EE over a 24-h period and activity energy expenditure (AEE) will be computed from TEE using an estimate of resting metabolic rate (0.9 TEE-RMR). This method will be developed in a sample of 50 normal-weight and 50 overweight children and adolescents using 24-h room respiration calorimetry, and validated in an independent sample (n=46) using 24-h room respiration calorimetry and 7-day free-living measurements of TEE by the doubly labeled water (DLW) method. The overall goal will be to predict 24-h TEE and AEE of individuals from combined HR and PA within 10% of independently measured values by respiration calorimetry and DLW. Therefore, the specific aims of the proposed project are: 1. To develop multivariate adaptive regression splines (MARS) and cross-sectional time series models for the prediction of EE and hence 24-h TEE and AEE from HR in 50 normal-weight and 50 overweight children and adolescents using Actiheart and 24-h room respiration calorimetry. 2. To validate the MARS and cross-sectional time series models for the prediction of minute-by-minute EE and hence 24-h TEE and AEE from HR against 24-h room respiration calorimetry and DLW method in an independent sample of 23 normal-weight and 23 overweight children and adolescents. Public Health Relevance: Free-living measurements of 24-h TEE and AEE are required to better understand the metabolic, physiological, behavioral and environmental factors affecting energy balance and contributing to the global epidemic of childhood obesity. The two primary methods to measure EE (respiration calorimetry and DLW) are impractical for the large-scale epidemiological studies required to address this important public health problem. A new method based on direct ambulatory monitoring of HR and PA will be developed to accurately predict EE, and hence 24-h TEE and AEE in children and adolescents. [unreadable] [unreadable]